In recent years, machine learning and data mining technologies have received growing attentions in the biomedical domain. Many of the biomedical applications, which deal with physiological and biomedical data, require person specific or person adaptive systems. The greatest challenge in developing such systems is the difference in data distributions between the persons or entities, making the task of modeling the data, challenging. As a result, despite the wide application of machine learning, efficient deployment of its principles to model the real world data is still a challenge. In this talk, I will present subject specific predictive and classification models for physiological and biomedical data based on novel transfer and active learning methods.

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